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1.61 MB

Extraction Summary

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Document Information

Type: Book page / investigative document
File Size: 1.61 MB
Summary

This document is page 122 from a book or manuscript titled 'Are the Androids Dreaming Yet?'. It discusses technical concepts regarding neural networks, 'back propagation,' and AI training. It also introduces a section on 'Quantum Brains,' citing Stuart Hameroff from the University of Arizona and his theories regarding tubulin and micro tubes in the brain. The document bears a Bates stamp 'HOUSE_OVERSIGHT_015812', indicating it was part of a document production for the House Oversight Committee, likely related to investigations into Jeffrey Epstein's connections with scientists and academia.

People (1)

Name Role Context
Stuart Hameroff Professor of Anesthesiology
Cited in the text regarding his theories on 'Quantum Brains' and tubulin as the fundamental information-processing un...

Organizations (2)

Name Type Context
University of Arizona
Employer of Stuart Hameroff.
House Oversight Committee
Implied by the Bates stamp 'HOUSE_OVERSIGHT_015812' at the bottom of the page.

Locations (1)

Location Context
Mentioned in relation to Stuart Hameroff.

Key Quotes (2)

"Strong AI proponents believe making a thinking machine is just a matter of building a really large, fast neural network and working out how to train it efficiently."
Source
HOUSE_OVERSIGHT_015812.jpg
Quote #1
"But, Stuart Hameroff, Professor of Anesthesiology at the University of Arizona, thinks neurons are not the fundamental information-processing unit in the brain. He suggests that this accolade should go to tubulin."
Source
HOUSE_OVERSIGHT_015812.jpg
Quote #2

Full Extracted Text

Complete text extracted from the document (2,482 characters)

122
Are the Androids Dreaming Yet?
inhibitors and activators like in real synapses. An individual neuron will fire if the sum of all the connections multiplied by the weights reaches a certain pre-determined threshold.
A neural network does not run a program in the conventional sense, and must be trained through experience rather like a human brain. The training process allows the weights in the network table to be adjusted to give the correct result. But, unlike the brain, you can read the weights and even save them to a disk. The neural network tables start with random settings. You show the network the letter 'A' and adjust the weights in the tables until it gives a positive answer: 'It's an A'. Repeat the process with the other letters until the network correctly distinguishes them. As you do this a computer algorithm constantly adjusts the weighting tables using a method called 'back propagation'.
At the end of the training process you can show the network some new input and see how it does. For example, a letter 'A' that is in a slightly different font to anything in the training set. Trained neural networks can perform complex tasks such as recognizing faces or making clinical diagnoses, and they can be allowed to modify their weighting tables as they work so they learn from experience in a similar way to a human brain. Strong AI proponents believe making a thinking machine is just a matter of building a really large, fast neural network and working out how to train it efficiently.
Quantum Brains
Conventional wisdom says each brain cell is a single processing unit making an on-off decision – fire, or don't fire – depending on the state of its neighbors. But, Stuart Hameroff, Professor of Anesthesiology at the University of Arizona, thinks neurons are not the fundamental information-processing unit in the brain. He suggests that this accolade should go to tubulin. Tubulin is a small, versatile protein that self-assembles into filaments rather like the way buckyballs – a magnetic children's toy – can be arranged. There are two types of tubulin molecule: α and β. They slot together and wrap around to form a micro tube about 25nm in diameter.
Tubulin micro tubes do several important things in the body. They form the skeleton of neurons and give them structure. They are involved in guiding neurons as they grow towards each other to form new connections, and they also operate in the nucleus of a cell to unzip
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